import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


A						=			logging.get_logger(__name__)

A						=			{'vocab_file': 'spiece.model'}

A						=			{
    'vocab_file': {
        'bert_for_seq_generation': (
            'https://huggingface.co/google/bert_for_seq_generation_L-24_bbc_encoder/resolve/main/spiece.model'
        ),
    }
}

A						=			{'bert_for_seq_generation': 5_1_2}





class     lowerCAmelCase__     (				SCREAMING_SNAKE_CASE_			):


		'''simple docstring'''






		lowerCAmelCase_     =   VOCAB_FILES_NAMES
		lowerCAmelCase_     =   PRETRAINED_VOCAB_FILES_MAP
		lowerCAmelCase_     =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		lowerCAmelCase_     =   []
		lowerCAmelCase_     =   ['input_ids', 'attention_mask']
		def __init__(       self     :     Optional[Any]     ,  snake_case__     :     List[Any]     ,  snake_case__     :     Optional[Any]="<s>"     ,  snake_case__     :     Union[str, Any]="</s>"     ,  snake_case__     :     int="<unk>"     ,  snake_case__     :     Optional[int]="<pad>"     ,  snake_case__     :     Dict="<::::>"     ,  snake_case__     :     Optional[Dict[str, Any]] = None     ,  **snake_case__     :     Optional[int]     ,  )      ->	None:
				_lowerCamelCase				   =  {} if sp_model_kwargs is None else sp_model_kwargs

				# Add extra_ids to the special token list
				super().__init__(
				    bos_token=snake_case__     ,  eos_token=snake_case__     ,  unk_token=snake_case__     ,  pad_token=snake_case__     ,  sep_token=snake_case__     ,  sp_model_kwargs=self.sp_model_kwargs     ,  **snake_case__     ,  )

				_lowerCamelCase				   =  vocab_file

				_lowerCamelCase				   =  spm.SentencePieceProcessor(**self.sp_model_kwargs		)
				self.sp_model.Load(snake_case__		)
		@property
		def   _snake_case       (       self     :     Optional[Any]		)      ->	List[str]:
				return self.sp_model.get_piece_size()
		def   _snake_case       (       self     :     Tuple		)      ->	int:
				_lowerCamelCase				   =  {self.convert_ids_to_tokens(snake_case__		): i for i in range(self.vocab_size		)}
				vocab.update(self.added_tokens_encoder		)
				return vocab
		def __getstate__(       self     :     Tuple		)      ->	Any:
				_lowerCamelCase				   =  self.__dict__.copy()
				_lowerCamelCase				   =  None
				return state
		def __setstate__(       self     :     Tuple     ,  snake_case__     :     Optional[int]		)      ->	Dict:
				_lowerCamelCase				   =  d

				# for backward compatibility
				if not hasattr(self     ,  'sp_model_kwargs'		):
						_lowerCamelCase				   =  {}

				_lowerCamelCase				   =  spm.SentencePieceProcessor(**self.sp_model_kwargs		)
				self.sp_model.Load(self.vocab_file		)
		def   _snake_case       (       self     :     Any     ,  snake_case__     :     str		)      ->	List[str]:
				return self.sp_model.encode(snake_case__     ,  out_type=snake_case__		)
		def   _snake_case       (       self     :     Optional[int]     ,  snake_case__     :     int		)      ->	Dict:
				return self.sp_model.piece_to_id(snake_case__		)
		def   _snake_case       (       self     :     Any     ,  snake_case__     :     Union[str, Any]		)      ->	Optional[int]:
				_lowerCamelCase				   =  self.sp_model.IdToPiece(snake_case__		)
				return token
		def   _snake_case       (       self     :     Union[str, Any]     ,  snake_case__     :     Optional[Any]		)      ->	List[str]:
				_lowerCamelCase				   =  []
				_lowerCamelCase				   =  ''
				for token in tokens:
						# make sure that special tokens are not decoded using sentencepiece model
						if token in self.all_special_tokens:
								out_string += self.sp_model.decode(snake_case__		) + token
								_lowerCamelCase				   =  []
						else:
								current_sub_tokens.append(snake_case__		)
				out_string += self.sp_model.decode(snake_case__		)
				return out_string.strip()



		def   _snake_case       (       self     :     Optional[Any]     ,  snake_case__     :     str     ,  snake_case__     :     Optional[str] = None		)      ->	Tuple[str]:
				if not os.path.isdir(snake_case__		):
						logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""		)
						return
				_lowerCamelCase				   =  os.path.join(
				    snake_case__     ,  (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']		)

				if os.path.abspath(self.vocab_file		) != os.path.abspath(snake_case__		) and os.path.isfile(self.vocab_file		):
						copyfile(self.vocab_file     ,  snake_case__		)
				elif not os.path.isfile(self.vocab_file		):
						with open(snake_case__     ,  'wb'		) as fi:
								_lowerCamelCase				   =  self.sp_model.serialized_model_proto()
								fi.write(snake_case__		)

				return (out_vocab_file,)
def 	lowerCamelCase					(	UpperCamelCase     :				int			,       UpperCamelCase     :				int							)   ->    float:
		return base * power(UpperCamelCase			,       (exponent - 1)							) if exponent else 1


if __name__ == "__main__":
				print('Raise base to the power of exponent using recursion...')
				A						=			int(input('Enter the base: ').strip())
				A						=			int(input('Enter the exponent: ').strip())
				A						=			power(base, abs(exponent))
				if exponent < 0:  # power() does not properly deal w/ negative exponents
								A						=			1 / result
				print(F'''{base} to the power of {exponent} is {result}''')